AB0617 PREDICTION OF MORTALITY USING CLUSTERS BASED ON CLINICAL AND LAB PARAMETERS: DATA FROM 2072 PATIENTS FROM INSPIRE COHORT
Authors: C. Kavadichanda, S. Ganapathy, D. Kounassegarane, L. Rajasekhar, B. Dhundra, A. Srivastava, S. Manuel, V. Shobha, B. Swarna, A. J. Mathew, D. Singh, M. Rathi, S. R. Tripathy, B. K. Das, M. D. Akhtar, R. Gupta, A. Jain, P. Ghosh, V. Negi, A. Aggarwal
Journal: Annals of the Rheumatic Diseases (2023)

<h3>Background</h3> Lupus is a heterogenous diseases which results in significant premature mortality. Most studies have evaluated risk factors for lupus mortality using regression models which considers the phenotype in isolation. Identifying clusters of patients on the other hand may help overcome the limitations of such analyses. <h3>Objectives</h3> The objectives of this study were to describe the causes of mortality and to analyze survival across clusters based on clinical phenotype and autoantibodies in patients of the Indian SLE Inception cohort for Research (INSPIRE) <h3>Methods</h3> Out of all patients, enrolled in the INSPIRE database till March 3st 2022, those who had &lt;10% missing variables in the clustering variables were included in the study. The cause of mortality and duration between the recruitment into the cohort and mortality was calculated. Agglomerative unsupervised hierarchical cluster analysis was performed using 25 variables that define SLE phenotype in clinical practice. The number of clusters were fixed using the elbow and silhouette methods. Survival rates were examined using Cox proportional hazards models: unadjusted, adjusted for age at disease onset, socio-economic status, steroid pulse, CYC, MMF usage and cluster of the patients. <h3>Results</h3> Indian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting.Out of 2211 patients in the cohort, 2072 were included into the analysis. The median (IQR) age of the patients was 26 (20-33) years and 91.7% were females. There were 288 (13.1%) patients with juvenile onset lupus. The median (range) duration of follow up of the patients was 37 (6-42) months. There were 170 deaths, with only 77 deaths occurring in a health care setting. Death within 6 months of enrollment occured in in 80 (47.1%) patients. Majority (n=87) succumbed to disease activity, 23 to infections, 24 to coexisting disease activity and infection and 21 to other causes. Pneumonia was the leading cause of death (n=24). Pneumococcal infection led to death in 11 patients and SARS-COV2 infection in 7 patients. The hierarchical clustering resulted in 4 clusters and the characteristics of these clusters are represented in a heatmap (Figure-1A,B). The mean (95% confidence interval [95% CI] survival was 39.17 (38.45-39.90), 39.52 (38.71-40.34), 37.73 (36.77-38.70) and 35.80 (34.10-37.49) months (p&lt;0.001) in clusters 1, 2, 3 and 4, respectively with an HR (95% CI) of 2.34 (1.56, 3.49) for cluster 4 with cluster 1 as reference(Figure 1C). The adjusted model showed an HR (95%CI) for cluster 4 of 2.22 (1.48, 3.22) with an HR(95%CI) of 1.78 (1.29, 2.45) for low socioeconomic status as opposed to a high socioeconomic status (Table 1). <h3>Conclusion</h3> Indian patients with lupus have significant early mortality and the majority of deaths occurs outside the hospital setting. Disease activity as determined by the traditional activity measures may not be sufficient to understand the true magnitude of organ involvement resulting in mortality. Clinically relevant clusters can help clinicians identify those at high risk for mortality with greater accuracy. <h3>REFERENCES:</h3> NIL. <h3>Acknowledgements:</h3> NIL. <h3>Disclosure of Interests</h3> None Declared.